Research on Feature Extraction Algorithm of Palm Main Line Based on Bottom Hat Transformation

Abstract

Aiming at the problem that the main line of palm is not easy to extract, and it is easy to be affected by illumination and uneven color of palm, this paper proposes a feature extraction algorithm based on base The bottom transformation. The bottom cap transform can eliminate the influence of uneven illumination and extract the main line of the palm. The collected palm image is first grayscaled and bottomed, and then binarized, the palm area is separated, the palm area is found, the palm boundary is separated by the Sobel edge detector, and the fingertip valley coordinates are determined. The palm area is divided, the knuckles and palm prints are found, and the vertical projection is used to match the palm print and the knuckle pattern. The experimental results show that the method can eliminate the influence of uneven illumination and uneven color of palm, and it has fast speed and strong anti-noise ability. It is suitable for large-scale palm database to achieve coarse screening.